Recently, dataless text classification, i.e., a new paradigm of weakly supervised learning, has attracted increasing attention from the community [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}, [9]}, [10]}, [11]}, [12]}, [13]}, [14]}. The target is to build text classifiers by training over unlabeled documents with predefined representative words of categories (called seed words), instead of labeled documents. Because manually selecting a small set of seed words for a given dataset is much cheaper than labeling all documents [4]}, the dataless method can effectively save many human efforts and become a promising supplement to traditional supervised text classifiers.
